<p>A visualization tool that provides an aggregate view of execution through a graph of events called the causality graph, which is suitable for systems with hundreds or thousands of processors, coarse-grained parallelism, and for a language that makes communication and synchronization explicit, is discussed. The methods for computing causality graphs and stepping through an execution with causality graphs are described. The properties of the abstraction algorithms and super nodes, the subgraphs in causality graphs, are also discussed.</p>